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Consider the discrete probability distribution shown here:

  1. Find μ=E(x).
  2. Find σ=E[(xμ)2]
  3. Find the probability that the value of x falls within one standard deviation of the mean. Compare this result to the Empirical Rule.

Short Answer

Expert verified
  1. 3.3
  2. 1.27
  3. 100%

Step by step solution

01

(a) Definition of a discrete probability distribution

A discrete probability distribution refers to a probability distribution where the count is finite. The outcomes mainly do not fall anywhere in the distribution on a continuum as they are finite.

02

Calculation of μ

The calculation μfor the given discrete probability distribution is shown below:

role="math" localid="1653629636380" μ=E(x)=E[xp(x)]=1(0.1)+2(0.2)+3(0.2)+4(0.3)+5(0.2)=0.1+0.4+0.6+1.2+1=3.3

03

(b) Definition of a discrete probability distribution

Discrete probability distributions include a finite number of observations. A typical example of this can be tossing a coin where everyone knows that there will be either of the two outcomes, head or tail.

04

Calculation of σ = E[(x−μ)2]

The calculation σ=E[(xμ)2]is shown below:

role="math" localid="1653630450721" σ=E[(xμ)2]=E[(xμ)2p(x)]=(1-3.3)×0.1+(23.3)×0.2+(33.3)×0.2+(43.3)×0.3+(53.3)×0.2=1.61

05

(c) Calculation of the interval

The calculation of the interval is shown below:

μ+2σ=3.3+2×1.27=5.84μ2σ=3.32×1.27=0.76

06

Calculation of the probability

As 0.76 is less than 1 and 5.84 is greater than 5, the calculation of probability via empirical rule must consider all the associated probabilities as shown below:

Probability=E[p(x)]×100=[(0.1)+(0.2)+(0.2)+(0.3)+(0.2)]×100=1×100=100%

It shows that as it is 100 percent, all the values lie within the interval.

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